Conversion of analog images into digital data has become widespread for a variety of applications, including storing, manipulating, transmitting and displaying or printing copies of the images. For example, sequences of frames from a motion picture film are often digitized, image enhancement or special effects are performed on the digitized images and the result written onto a blank film. Also, images captured on photographic media are being converted to digital data and stored on compact discs for readout and display as a video image or for printing with various types of color printers. In order to capture the photographic image digitally, the film frame is scanned with a light beam, and the light transmitted through the film is detected, typically as three primary color light intensity signals, and digitized. The digitized values may be formatted to a standard for video display and stored on compact disc or magnetic media. Such film digitizers take a variety of forms and the various common aspects of film digitizing, particularly line illumination and linear CCD-based digitizers, are described in greater detail in commonly assigned U.S. Pat. No. 5,012,346. Also photographic prints can be digitized using reflection scanners.
Providing new pixel values for corrupted or defect pixels is a common operation in digital image processing. Part of the image can be damaged by scratches or degraded by dust. Corrupted pixel values do not represent original image information and hence these values cannot be used for restoration purposes. New pixel values must be supplied consistent with the image content surrounding the area to be replaced. This process is referred to here as a pixelfill. Another example of an image processing operation requiring pixelfill is an object removal from the image, for example rig and wire removal in motion pictures.
Simple nondirectional averaging or erosion techniques are usually used to fill small, compact defect regions in a film frame. These methods produce undesired smoothness in the replaced regions and severely distort edges that are intersected by the regions to be filled. The problem of reconstructing edges is especially important for long, narrow regions to be filled due to the high probability they intersect multiple objects in the image. This problem is addressed in the method described by massmann et al. in U.S. Pat. No. 5,097,521. The above method has some disadvantages. First, it assumes essentially vertical regions to be filled. It may also not handle well the situation where multiple edges intersect in the defect region.
Kwok et al. in U.S. Pat. No. 5,097,521 disclose an error concealment system based on the gradient field. In this system a two dimensional block of defect data is filled. This system may not handle well the case where objects crossing the defect block have a width much smaller than the size of the defect block.
Previous methods can produce artifacts when curved edges, object corners or "T-type" edge intersections are covered by the defect region.
It would be desirable then, to have a method of providing corrected pixel values for pixels in a defect region, which can produce reconstructed image content in the defect region which is fairly consistent with the image content of the surrounding area, even in the case where the defect region intersects objects with a width smaller than, or comparable to, the width of the defect region or where multiple edges intersect in the defect region.